Data Warehousing & Enterprise Data Management (EDM)
Flashback <~~~ Back in 2015, I devoted countless hours learning about the significance of Big Data & Data Modeling techniques, Kimball’s Dimensional Modeling methodologies, Extract, Transform and Load (ETL) best practices and lessons learned, and the comprehensive life cycle associated with Enterprise Data Management (EDM).
Now that I provided you with some background context for my story, I want to revisit the term #datawarehouse and discuss the continued importance of this timeless capability.
For starters…What is a Data Warehouse?
A Data Warehouse (DW) is either an on-premise or cloud based technology that stores structured and unstructured data from a variety of sources to provide meaningful business insights. A DW is at the core of all Business Intelligence (BI) frameworks, which are built for data governance, analysis, visualization, and reporting.
Now, fast forward five years since the time I read that book (2020), data warehousing is not only a leading topic among Business Intelligence solutions but it seems that it’s becoming more popular by the day. For instance, one of my favorite sources for good insights comes from the company, G2. G2 provides consumers with awesome software technology reviews within the Business Intelligence (BI) landscape. In this case, check out their reviews on the Top Data Warehouse Software in 2020.Screen Shot
With great market research techniques, G2 provides a wholistic overview of the DW landscape based on pros/cons of the software offerings and most of the market competitors.
6 Reasons to use data warehouse solutions:
Improved migration solutions from on-premise to cloud architectures;
Flexible pricing models; Most impressive (to me) for cloud-based is the ‘pay-to-play’;
Improved security measures for data privacy; on-premise & cloud;
Improved data availability/accessibility features; self-service analytics at all levels of business operations;
Data Warehousing-as-a-Service (DWaaS); reduce data admin needs;
Automated ‘Big Data’ integration solutions, which helps shift focus from data cleansing and management to advanced analytics.
As you can see, data warehousing is still a thing in today’s growing BI landscape. Although some organizations still haven’t scratched the surface on HOW data warehouse capabilities can support their digital transformation efforts, there’s plenty of options when they decide to make that decision for future growth.
What’s your company’s data warehouse solution?
If you don’t have one in place you may want to consider looking into one of the leading brands provided in the G2 review to help with BI needs.